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Essay for HCI

1 Introduction

Hello HCI team,

My name is Joseph, and it’s a pleasure to be a volunteer with the Happy City Index.

Before watching the video instruction, I had several questions and ideas. My two main ones are:

  1. Gathering data from Reddit and applying sentiment analysis to discover how citizens feel about their city over time.

  2. Gathering online resources on price changes for certain items, as I demonstrated in the report below.

I look forward to collaborating with everyone who shares the same passion.

Show the code
import plotly.express as px
import polars as pl
from pathlib import Path
import numpy as np
import plotly.io as pio
pio.renderers.default = 'jupyterlab+notebook'
pio.templates.default = "plotly_white"
Show the code
path_db = Path.cwd()/'outputs'/'04_db.parquet'
Show the code
df = pl.read_parquet(path_db)
Show the code
df_i = df['item'].value_counts().sort('count')
df_i_f = df_i.filter(pl.col('count').gt(pl.col('count').quantile(0.7)))
Show the code
df_f = df.filter(pl.col('item').is_in(df_i_f['item'].to_list())).sort(['year','category','item'])

2 Price change from cost of living index - samle

2.1 Category: Buy Apartment Price

2.1.1 Item: Price per Square Feet to Buy Apartment Outside of Centre

2.1.2 Item: Price per Square Feet to Buy Apartment in City Centre

2.2 Category: Childcare

2.2.1 Item: International Primary School, Yearly for 1 Child

2.2.2 Item: Preschool (or Kindergarten), Full Day, Private, Monthly for 1 Child

2.3 Category: Clothing And Shoes

2.3.1 Item: 1 Pair of Jeans (Levis 501 Or Similar)

2.3.2 Item: 1 Pair of Men Leather Business Shoes

2.3.3 Item: 1 Pair of Nike Running Shoes (Mid-Range)

2.3.4 Item: 1 Summer Dress in a Chain Store (Zara, H&M, …)

2.4 Category: Markets

2.4.1 Item: Apples (1 lb)

2.4.2 Item: Banana (1 lb)

2.4.3 Item: Beef Round (1 lb) (or Equivalent Back Leg Red Meat)

2.4.4 Item: Bottle of Wine (Mid-Range)

2.4.5 Item: Cigarettes 20 Pack (Marlboro)

2.4.6 Item: Domestic Beer (0.5 liter bottle)

2.4.7 Item: Eggs (regular) (12)

2.4.8 Item: Imported Beer (12 oz small bottle)

2.4.9 Item: Lettuce (1 head)

2.4.10 Item: Loaf of Fresh White Bread (1 lb)

2.4.11 Item: Local Cheese (1 lb)

2.4.12 Item: Milk (regular), (1 gallon)

2.4.13 Item: Onion (1 lb)

2.4.14 Item: Oranges (1 lb)

2.4.15 Item: Potato (1 lb)

2.4.16 Item: Rice (white), (1 lb)

2.4.17 Item: Tomato (1 lb)

2.4.18 Item: Water (1.5 liter bottle)

2.5 Category: Rent Per Month

2.5.1 Item: Apartment (1 bedroom) Outside of Centre

2.5.2 Item: Apartment (1 bedroom) in City Centre

2.5.3 Item: Apartment (3 bedrooms) Outside of Centre

2.5.4 Item: Apartment (3 bedrooms) in City Centre

2.6 Category: Restaurants

2.6.1 Item: Cappuccino (regular)

2.6.2 Item: Imported Beer (12 oz small bottle)

2.6.3 Item: McMeal at McDonalds (or Equivalent Combo Meal)

2.6.4 Item: Meal for 2 People, Mid-range Restaurant, Three-course

2.6.5 Item: Meal, Inexpensive Restaurant

2.7 Category: Salaries And Financing

2.7.1 Item: Average Monthly Net Salary (After Tax)

2.7.2 Item: Mortgage Interest Rate in Percentages (%), Yearly, for 20 Years Fixed-Rate

2.8 Category: Sports And Leisure

2.8.1 Item: Cinema, International Release, 1 Seat

2.8.2 Item: Fitness Club, Monthly Fee for 1 Adult

2.8.3 Item: Tennis Court Rent (1 Hour on Weekend)

2.9 Category: Transportation

2.9.1 Item: Gasoline (1 gallon)

2.9.2 Item: Monthly Pass (Regular Price)

2.9.3 Item: One-way Ticket (Local Transport)

2.9.4 Item: Taxi 1 mile (Normal Tariff)

2.9.5 Item: Taxi 1hour Waiting (Normal Tariff)

2.9.6 Item: Taxi Start (Normal Tariff)

2.9.7 Item: Volkswagen Golf 1.4 90 KW Trendline (Or Equivalent New Car)

2.10 Category: Utilities (Monthly)

2.10.1 Item: 1 min. of Prepaid Mobile Tariff Local (No Discounts or Plans)

2.10.2 Item: Basic (Electricity, Heating, Cooling, Water, Garbage) for 915 sq ft Apartment

2.10.3 Item: Internet (60 Mbps or More, Unlimited Data, Cable/ADSL)